Abstract
Benchmarks have shown to be an important tool to advance science in the fields of information analysis and retrieval. Problems of running benchmarks include obtaining large amounts of data, annotating it and then distributing it to the participants of a benchmark. Distribution of the data to participants is currently mostly done via data download that can take hours for large data sets and in countries with slow Internet connections even days. Sending physical hard disks was also used for distributing very large scale data sets (for example by TRECvid) but also this becomes infeasible if the data sets reach sizes of 5–10 TB. With cloud computing it is possible to make very large data sets available in a central place with limited costs. Instead of distributing the data to the participants, the participants can compute their algorithms on virtual machines of the cloud providers. This text presents reflections and ideas of a concrete project on using cloud–based benchmarking paradigms for medical image analysis and retrieval. It is planned to run two evaluation campaigns in 2013 and 2014 using the proposed technology.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alonso, O., Rose, D.E., Stewart, B.: Crowdsourcing for relevance evaluation. ACM SIGIR Forum 42(2), 9–15 (2008)
Buyya, R., Yeo, C.S., Venugopal, S.: Market–oriented cloud computing: Vision, hype, and reality for delivering it services as computing utilities. In: 10th IEEE International Conference on High Performance Computing and Communications, pp. 5–13. IEEE (2008)
Everingham, M., Zisserman, A., Williams, C.K.I., Van Gool, L., Allan, M., Bishop, C.M., Chapelle, O., Dalal, N., Deselaers, T., Dorkó, G., Duffner, S., Eichhorn, J., Farquhar, J.D.R., Fritz, M., Garcia, C., Griffiths, T., Jurie, F., Keysers, D., Koskela, M., Laaksonen, J., Larlus, D., Leibe, B., Meng, H., Ney, H., Schiele, B., Schmid, C., Seemann, E., Shawe-Taylor, J., Storkey, A.J., Szedmak, S., Triggs, B., Ulusoy, I., Viitaniemi, V., Zhang, J.: The 2005 PASCAL Visual Object Classes Challenge. In: Quiñonero-Candela, J., Dagan, I., Magnini, B., d’Alché-Buc, F. (eds.) MLCW 2005. LNCS (LNAI), vol. 3944, pp. 117–176. Springer, Heidelberg (2006)
Harman, D.: Overview of the first Text REtrieval Conference (TREC–1). In: Proceedings of the First Text REtrieval Conference (TREC–1), Washington DC, USA, pp. 1–20 (1992)
Müller, H., Clough, P., Deselaers, T., Caputo, B. (eds.): ImageCLEF – Experimental Evaluation in Visual Information Retrieval. The Springer International Series On Information Retrieval, vol. 32. Springer, Heidelberg (2010)
Rowe, B.R., Wood, D.W., Link, A.N., Simoni, D.A.: Economic impact assessment of NIST’s Text REtrieval Conference (TREC) Program. Tech. Rep. Project Number 0211875, RTI International (2010)
Smeaton, A.F., Kraaij, W., Over, P.: TRECVID 2003: An overview. In: Proceedings of the TRECVID 2003 Conference (December 2003)
Thornley, C.V., Johnson, A.C., Smeaton, A.F., Lee, H.: The scholarly impact of TRECVid (2003–2009). JASIST 62(4), 613–627 (2011)
Tsikrika, T., Seco de Herrera, A.G., Müller, H.: Assessing the Scholarly Impact of ImageCLEF. In: Forner, P., Gonzalo, J., Kekäläinen, J., Lalmas, M., de Rijke, M. (eds.) CLEF 2011. LNCS, vol. 6941, pp. 95–106. Springer, Heidelberg (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hanbury, A., Müller, H., Langs, G., Weber, M.A., Menze, B.H., Fernandez, T.S. (2012). Bringing the Algorithms to the Data: Cloud–Based Benchmarking for Medical Image Analysis. In: Catarci, T., Forner, P., Hiemstra, D., Peñas, A., Santucci, G. (eds) Information Access Evaluation. Multilinguality, Multimodality, and Visual Analytics. CLEF 2012. Lecture Notes in Computer Science, vol 7488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33247-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-33247-0_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33246-3
Online ISBN: 978-3-642-33247-0
eBook Packages: Computer ScienceComputer Science (R0)